Articles by Mauro Cesa
Machines can read, but do they understand?
A novel NLP application built on a Google transformer model can help predict ratings transitions
Podcast: NYU’s Kolm on transaction costs and machine learning
TCA methodologies that ignore partial fills “might be off by 20% to 30%”
Podcast: Colin Turfus on short-rate models and Libor’s end
Deutsche Bank quant proposes a lean model to quickly produce benchmark prices
Derivatives pricing starts feeling the heat of climate change
Quants find physical and transition risks can lead to significant rise in CVA
Podcast: Claudio Albanese on how bad models survive
Darwin’s theory of natural selection could help quants detect flawed models and strategies
The case for reinforcement learning in quant finance
The technology behind Google’s AlphaGo has been strangely overlooked by quants
Deep XVAs and the promise of super-fast pricing
Intelligent robots can value complex derivatives in minutes rather than hours
Synthetic data enters its Cubist phase
Quants are using the theory of rough paths to distil the essence of financial datasets
Podcast: Piterbarg on medians and machine learning
How the Libor transition inspired NatWest quant’s latest paper on exotic derivatives valuation
Podcast: Hagan on convexity, volatility and the London Whale
Ex-JP Morgan quant discusses his latest work and the risk failures that cost the bank $6bn in 2012
Podcast: Barclays’ Ben Burnett on how banks can implement HVA
New valuation adjustment may lead to more efficient management of derivatives books
A look at future exposures, through a 19th century lens
Can a centenarian maths idea speed up the calculation of forward sensitivities?
The volatility paradigm that’s stirring up options pricing
‘Rough volatility’ models promise better pricing and hedging of options. But will they catch on?
Deep hedging strays when volatility gets rough – study
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging
Podcast: Richard Martin on improving credit migration models
Star quant proposes a new model for predicting changes in bond ratings
Put options power up variable annuities
Insurance quants increase risk-adjusted profits using novel hedging technique
Putting the H in XVAs
Barclays quant proposes methodology for factoring hedging costs into derivatives valuations
Setting boundaries for neural networks
Quants unveil new technique for controlling extrapolation by neural networks
A guiding light for corporates lost in the fog of XVAs
Chris Kenyon proposes a framework for optimising XVAs – from the client perspective
Podcast: Matthias Arnsdorf on a new – and cheaper – KVA
Quant proposes approach anchored by a dealer’s default rate rather than its return on equity
Breaking barriers in options pricing
A new technique for pricing exotic options unifies two classic models
Danske quants discover speedier way to crunch XVAs
Differential machine learning produces results “thousands of times faster and with similar accuracy”
Time to move on from mean-variance diversification
A new diversification measure appears to produce better results than mean-variance optimisation
Podcast: CFM’s Bouchaud on agent-based models and ESG investing
Hedge fund quant, and Risk.net’s new columnist, shares his unique take on markets